
A new model is proposed for synthetic document image generation guided by the layout of a reference sample.

Qualitative and quantitative results on the PubLayNet dataset [1]}, demonstrate our model's capability to generate complex layout documents with respect to spatial and semantic information of object categories.

Also this work addresses the layout-guided document image synthesis task with an analytical understanding as the first of its kind in the document analysis community.

